A small, opinionated HerdR launcher for my current workflow.

The idea is simple: from any Git repository, run herd and spawn a ready-to-use HerdR workspace with one agent tab powered by omp.sh, plus editor, runner, terminal and git tabs.

The tabs look like this:

🤖 agent | 📝 editor | 🌿 changes | 🔀 diff | 🏃 run | 🖥️ term

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

1. Follow standard conventions.
2. Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
3. Boy scout rule. Leave the campground cleaner than you found it.
4. Always find root cause. Always look for the root cause of a problem.

Following are the extensions required for neovim:

• mason
• mason-lspconfig
• lspconfig

All the boxes are single/two cell tables or two row tables.

A free, beginner-friendly calisthenics program you can do at home with no gym or equipment required.

3 days per week • ~60 minutes per session • Build strength & muscle with bodyweight exercises

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.